How will this help me?

Getting to know messy data is... well, messy.

Exploratory data analysis is a critical part of any data project but is often a painful and frustrating process.
Data engineers and data scientists waste valuable time writing code to load data, extract basic summary statistics, create visualizations, and reshape data.
This process is often done in an ad hoc way thus making deployment to a scalable infrastructure or any production like system a time and resource intensive project.

Who is this for?

Anyone and everyone that needs to handle messy data. Our data visualization and inspection tools are built into Jupyter notebook so you can get started in just a few lines of code.
We've also built a set of :ref:`transforms_link` that reduce the amount of code you need to write to get to the same transforms while still being flexible and transparent.

How does Datamode help?

Datamode is built for anyone that needs to quickly undestand data, reshape variables, and push these transforms into a
production pipeline. Developers can write and execute code in their Jupyter notebooks and deploy that same code to be used in a scalable environment.